def data_standardize_money163(stock_code, index_code='000001.SH'): # 1.读取万得的股票数据 stock_data = Functions.import_stock_data_money163(stock_code) # 2.读取指数数据 index_data = Functions.import_index_data_wande(index_code=index_code) # 3.个股数据除权处理, 默认后复权,直接替换OLHC列 stock_data = Functions.cal_adjust_price(stock_data) # 3.合并个股数据和指数数据 stock_data = Functions.merge_with_index_data(stock_data, index_data) # 4.添加涨跌停列 stock_data = Functions.limit_up_down(stock_data) return stock_data
def data_standardize_xbx(code): # 1.读取万得的股票数据 stock_data = Functions.import_stock_data_xbx(code) # 2.读取指数数据 index_data = Functions.import_index_data_xbx() # 3.个股数据除权处理, 默认后复权,直接替换OLHC列 stock_data = Functions.cal_adjust_price(stock_data) # 3.合并个股数据和指数数据 stock_data = Functions.merge_with_index_data(stock_data, index_data) # 4.添加涨跌停列 stock_data = Functions.limit_up_down(stock_data) return stock_data
def data_standardize_money163(df, index_code='000001.SH', return_type=1, start_date='19890101'): # 1.读取万得的股票数据 # stock_data = Functions.import_stock_data_money163(stock_code) stock_data = df.copy() # 2.读取指数数据 index_data = Functions.import_index_data_wande(index_code=index_code) # 3.个股数据除权处理, 默认后复权,直接替换OLHC列 stock_data = Functions.cal_adjust_price(stock_data, return_type=return_type) # 3.合并个股数据和指数数据 stock_data = Functions.merge_with_index_data(stock_data, index_data) # 4.添加涨跌停列 stock_data = Functions.limit_up_down(stock_data) # 取得指定时间范围的数据 stock_data = stock_data[stock_data['date'] >= pd.to_datetime(start_date)] return stock_data
# print Functions.get_stock_code_list_in_one_dir_wande(file_path) # 4.2 从xbx的数据读取股票列表 file_path = 'D:/all_trading_data/data/input_data/stock_data' # print Functions.get_stock_code_list_in_one_dir_xbx(file_path) # exit() # ==== 5 个股数据和指数数据合并,日周期 stock_data = Functions.merge_with_index_data(stock_data_adjust, index_data) # print stock_data # exit() # ==== 6 周期转换 stock_data = Functions.transfer_to_period_data(stock_data, period_type='m') print stock_data exit() # print stock_data # 涨跌停信号添加 stock_data = Functions.limit_up_down(stock_data) # stock_data.ix[stock_data['open'] > stock_data['close'].shift(1) * 1.097, 'limit_up'] = 1 print stock_data exit() # 获得所有股票数据 # df = Functions.get_all_stock_data(load_type='orginal') # print df import random random = random.random() print random